scholarly journals A Framework to Analyse and Interpret Mouse Functional Genome by Prioritizing High Impact SNPs

2020 ◽  
Author(s):  
Ahmed Arslan
Keyword(s):  
Allelic Variation ◽  
Association Studies ◽  
Inbred Mice ◽  
Computational Method ◽  
Hypergeometric Test ◽  
Regulatory Regions ◽  
Functional Regions ◽  
Regulatory Impact ◽  
Genome Association ◽  
Biological Phenotype

The essential understanding of disease pathogenesis and enabling genetic findings to be used for developing new therapeutics, is missing in the identifications of genomic loci through whole genome association studies (GWAS). Here we describe a new computational method (mMap) that reduces this gap by characterizing the functional and regulatory impact of allelic variation. The method incorporates the precomputed annotations of 26 protein functional regions and eight regulatory regions and recover SNPs that fall/lie in these regions. After annotating SNPs to functional or regulatory data, method link them to biological functions and pathways, and predicts significantly disrupted biological regions, processes and pathways, by controlling false discovery through hypergeometric test. By doing so, the method limits data to human interpretation level by prioritizing SNPs that have the potential to mediate a biological phenotype. The method is applicable to procedures that rely on the understanding of the biological causal role of mouse SNPs and is available online. In two example mMap applications, including whole genomes SNPs data from 48 inbred mice strains, we identify biological mechanisms by which SNPs can regulate pathways to govern phenotypes by targeting different coding and regulatory regions, even in closely related strains.

scholarly journals Sampling strategies for whole genome association studies in aquaculture and outcrossing plant species

2009 ◽  
Vol 91 (6) ◽  
pp. 367-371 ◽  
Author(s):  
B. J. HAYES ◽  
I. M. MACLEOD ◽  
M. BARANSKI
Keyword(s):  
Plant Species ◽  
Association Studies ◽  
Whole Genome ◽  
Minimal Effect ◽  
Sampling Strategies ◽  
False Discovery ◽  
Breeding Populations ◽  
Genome Association ◽  
Whole Genome Association ◽  
Sib Families

SummaryA number of farmed species are characterized by breeding populations of large full-sib families, including aquaculture species and outcrossing plant species. Whole genome association studies in such species must account for stratification arising from the full-sib family structure to avoid high rates of false discovery. Here, we demonstrate the value of selective genotyping strategies which balance the contribution of families across high and low phenotypes to greatly reduce rates of false discovery with a minimal effect on power.

scholarly journals Individualized VDJ recombination predisposes the available Ig sequence space

2021 ◽  
Author(s):  
Andrei Slabodkin ◽  
Maria Chernigovskaya ◽  
Ivana Mikocziova ◽  
Rahmad Akbar ◽  
Lonneke Scheffer ◽  
...  
Keyword(s):  
Sequence Space ◽  
Distance Measure ◽  
Allelic Variation ◽  
Inbred Mice ◽  
Individualized Medicine ◽  
Monozygotic Twins ◽  
Antigen Recognition ◽  
Sequencing Data ◽  
Vdj Recombination ◽  
Individual Comparison

The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire, and consequently (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual-specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also non-genetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.

Abstract 439: Trajectory Analysis of Left Ventricular Dimensions From Biobank Data Uncovers Novel Genetic Associations

2020 ◽  
Vol 127 (Suppl_1) ◽  
Author(s):  
Tess Pottinger ◽  
Megan J Puckelwartz ◽  
Lorenzo L Pesce ◽  
Anthony Gacita ◽  
Isabella Salamone ◽  
...  
Keyword(s):  
Heart Failure ◽  
Longitudinal Data ◽  
Association Studies ◽  
The United States ◽  
Left Ventricular ◽  
Genome Wide Association Studies ◽  
Qtc Interval ◽  
Regulatory Regions ◽  
Genome Wide ◽  
Over Time

Background: Approximately 6 million adults in the United States have heart failure. The progression of heart failure is variable arising from differences in sex, age, genetic background including ancestry, and medication response. Many population-based genetic studies of heart failure have been cross-sectional in nature, failing to gain additional power from longitudinal analyses. As heart failure is known to change over time, using longitudinal data trajectories as a quantitative trait will increase power in genome wide association studies (GWAS). Methods: We used the electronic health record in a racially and ethnically diverse medical biobank from a single, metropolitan US center. We used whole genome data from 896 unrelated participants analyzed, including 494 who had at least 1 electrocardiogram and 324 who had more than 1 echocardiogram (average of 3 observations per person). A mixture model based semiparametric latent growth curve model was used to cluster outcome measures used for genome-wide analyses. Results: GWAS on the trajectory probability of QTc interval identified significant associations with variants in regulatory regions proximal to the WLS gene, which encodes Wntless, a Wnt ligand secretion mediator. WLS was previously associated with QTc and myocardial infarction, thus confirming the power of the method. GWAS on the trajectory probability of left ventricular diameter (LVIDd) identified significant associations with variants in regulatory regions near MYO10 , which encodes unconventional Myosin-10. MYO10 was previously associated with obesity and metabolic syndrome. Conclusions: This is the first study to show an association with variants in or near MYO10 and left ventricular dimension changes over time. Further, we found that using trajectory probabilities can provide increased power to find novel associations with longitudinal data. This reduces the need for larger cohorts, and increases yield from smaller, well-phenotyped cohorts, such as those found in biobanks. This approach should be useful in the study of rare diseases and underrepresented populations.

scholarly journals Calibrating the Performance of SNP Arrays for Whole-Genome Association Studies

PLoS Genetics ◽  
2008 ◽  
Vol 4 (6) ◽  
pp. e1000109 ◽  
Author(s):  
Ke Hao ◽  
Eric E. Schadt ◽  
John D. Storey
Keyword(s):  
Association Studies ◽  
Whole Genome ◽  
Snp Arrays ◽  
Genome Association ◽  
Whole Genome Association

scholarly journals TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes

2019 ◽  
Vol 47 (14) ◽  
pp. e79-e79
Author(s):  
Aitor González ◽  
Marie Artufel ◽  
Pascal Rihet
Keyword(s):  
Cleft Lip ◽  
Association Studies ◽  
Area Under The Curve ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Functional Snps ◽  
Functional Regions ◽  
Complex Phenotypes ◽  
Genome Wide ◽  
Intergenic Regions

Abstract Genome-wide association studies (GWAS) associate single nucleotide polymorphisms (SNPs) to complex phenotypes. Most human SNPs fall in non-coding regions and are likely regulatory SNPs, but linkage disequilibrium (LD) blocks make it difficult to distinguish functional SNPs. Therefore, putative functional SNPs are usually annotated with molecular markers of gene regulatory regions and prioritized with dedicated prediction tools. We integrated associated SNPs, LD blocks and regulatory features into a supervised model called TAGOOS (TAG SNP bOOSting) and computed scores genome-wide. The TAGOOS scores enriched and prioritized unseen associated SNPs with an odds ratio of 4.3 and 3.5 and an area under the curve (AUC) of 0.65 and 0.6 for intronic and intergenic regions, respectively. The TAGOOS score was correlated with the maximal significance of associated SNPs and expression quantitative trait loci (eQTLs) and with the number of biological samples annotated for key regulatory features. Analysis of loci and regions associated to cleft lip and human adult height phenotypes recovered known functional loci and predicted new functional loci enriched in transcriptions factors related to the phenotypes. In conclusion, we trained a supervised model based on associated SNPs to prioritize putative functional regions. The TAGOOS scores, annotations and UCSC genome tracks are available here: https://tagoos.readthedocs.io.

scholarly journals Effect of Disease-Associated Germline Mutations on Structure Function Relationship of DNA Methyltransferases

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 369 ◽  
Author(s):  
Allison B. Norvil ◽  
Debapriya Saha ◽  
Mohd Saleem Dar ◽  
Humaira Gowher
Keyword(s):  
Dna Methylation ◽  
Association Studies ◽  
Large Body ◽  
Genetic Alterations ◽  
Dna Methyltransferases ◽  
Neurological Dysfunction ◽  
Genome Association ◽  
Hereditary Disorders ◽  
Aberrant Dna Methylation ◽  
Function Relationship

Despite a large body of evidence supporting the role of aberrant DNA methylation in etiology of several human diseases, the fundamental mechanisms that regulate the activity of mammalian DNA methyltransferases (DNMTs) are not fully understood. Recent advances in whole genome association studies have helped identify mutations and genetic alterations of DNMTs in various diseases that have a potential to affect the biological function and activity of these enzymes. Several of these mutations are germline-transmitted and associated with a number of hereditary disorders, which are potentially caused by aberrant DNA methylation patterns in the regulatory compartments of the genome. These hereditary disorders usually cause neurological dysfunction, growth defects, and inherited cancers. Biochemical and biological characterization of DNMT variants can reveal the molecular mechanism of these enzymes and give insights on their specific functions. In this review, we introduce roles and regulation of DNA methylation and DNMTs. We discuss DNMT mutations that are associated with rare diseases, the characterized effects of these mutations on enzyme activity and provide insights on their potential effects based on the known crystal structure of these proteins.

scholarly journals Coevolutionary Dynamics of Rice Blast Resistance Gene Pi-ta and Magnaporthe oryzae Avirulence Gene AVR-Pita 1

2016 ◽  
Vol 106 (7) ◽  
pp. 676-683 ◽  
Author(s):  
Yulin Jia ◽  
Erxun Zhou ◽  
Seonghee Lee ◽  
Tracy Bianco
Keyword(s):  
Magnaporthe Oryzae ◽  
Marker Assisted Selection ◽  
Defense Mechanism ◽  
Allelic Variation ◽  
Blast Resistance ◽  
Quantitative Resistance ◽  
Association Studies ◽  
The United States ◽  
Avirulence Gene ◽  
Genome Wide Association Studies

The Pi-ta gene in rice is effective in preventing infections by Magnaporthe oryzae strains that contain the corresponding avirulence gene, AVR-Pita1. Diverse haplotypes of AVR-Pita1 have been identified from isolates of M. oryzae from rice production areas in the United States and worldwide. DNA sequencing and mapping studies have revealed that AVR-Pita1 is highly unstable, while expression analysis and quantitative resistance loci mapping of the Pi-ta locus revealed complex evolutionary mechanisms of Pi-ta-mediated resistance. Among these studies, several Pi-ta transcripts were identified, most of which are probably derived from alternative splicing and exon skipping, which could produce functional resistance proteins that support a new concept of coevolution of Pi-ta and AVR-Pita1. User-friendly DNA markers for Pi-ta have been developed to support marker-assisted selection, and development of new rice varieties with the Pi-ta markers. Genome-wide association studies revealed a link between Pi-ta-mediated resistance and yield components suggesting that rice has evolved a complicated defense mechanism against the blast fungus. In this review, we detail the current understanding of Pi-ta allelic variation, its linkage with rice productivity, AVR-Pita allelic variation, and the coevolution of Pi-ta and AVR-Pita in Oryza species and M. oryzae populations, respectively. We also review the genetic and molecular basis of Pi-ta and AVR-Pita interaction, and its value in marker-assisted selection and engineering resistance.

scholarly journals Power and SNP tagging in whole mitochondrial genome association studies

2008 ◽  
Vol 18 (6) ◽  
pp. 911-917 ◽  
Author(s):  
A. F. McRae ◽  
E. M. Byrne ◽  
Z. Z. Zhao ◽  
G. W. Montgomery ◽  
P. M. Visscher
Keyword(s):  
Mitochondrial Genome ◽  
Association Studies ◽  
Genome Association
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